Xiaojuan Ma

5.0k citations
196 papers · 2.9k indexed · h-index 28

Impact in

Papers in

Xiaojuan Ma

182 papers receiving 2.8k citations

Peers

Xiaojuan Ma
Comparison fields: 5 of 139
  • Computer Science Applications 607
  • Transportation 487
  • Human-Computer Interaction 397
  • Computer Vision and Pattern Recognition 635
  • Artificial Intelligence 973
Replace Daniele Quercia with:
Daniele Quercia United Kingdom
Alan Borning United States
Uichin Lee South Korea
Paola Salomoni Italy
Jorge Gonçalves Australia
Bruno Lepri Italy
Mirco Musolesi United Kingdom
Tsvi Kuflik Israel
Allison Woodruff United States
Catia Prandi Italy
Xiaojuan Ma relative to Daniele Quercia United Kingdom Daniele Quercia's profile →
Citations per field
00.5×3.3×
Daniele Quercia · 1×
Citations per year

Countries citing papers authored by Xiaojuan Ma

Since Specialization
Citations

This map shows the geographic impact of Xiaojuan Ma's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaojuan Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojuan Ma more than expected).

Fields of papers citing papers by Xiaojuan Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaojuan Ma. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaojuan Ma. The network helps show where Xiaojuan Ma may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Xiaojuan Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaojuan Ma Line = papers co-authored together Xiaojuan Ma links everyone, so they are left out of the graph.

All Works

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A Guided Tour of Literature Review:Facilitating Academic Paper Reading with Narrative Visualization
20162

About Xiaojuan Ma

Xiaojuan Ma is a scholar working on Human-Computer Interaction, Computer Science Applications, Computer Vision and Pattern Recognition, Transportation and Artificial Intelligence, having authored 196 papers that have together received 2.9k indexed citations. Recurring topics across this work include Data Visualization and Analytics (23 papers), Human Mobility and Location-Based Analysis (17 papers), Innovative Human-Technology Interaction (17 papers), Topic Modeling (15 papers), Video Analysis and Summarization (14 papers), Mobile Crowdsensing and Crowdsourcing (14 papers), Speech and dialogue systems (13 papers) and Multimodal Machine Learning Applications (13 papers). The work is most often cited by research in Computer Science Applications (607 citations), Transportation (487 citations), Human-Computer Interaction (397 citations), Computer Vision and Pattern Recognition (635 citations) and Artificial Intelligence (973 citations). Xiaojuan Ma has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Leye Wang, Daqing Zhang, Dingqi Yang, Bin Guo, Xiao Han, Huamin Qu, Zhenhui Peng, Chao Chen, Ziming Wu and Gang Pan. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Intelligent Transportation Systems, International Journal of Human-Computer Studies and ACM Transactions on Computer-Human Interaction.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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